OFDM System with Reverse Link Interference Estimation

ABSTRACT

A new method of performing interference estimation to allow the data packets to be efficiently delivered in an OFDM system. The interference estimation is performed on average over each frame for each mobile station individually in both frequency and time domains. Based on the estimated interference, the CIR can be determined by the BTS based on channel response estimates made by the BTS, or by the MS based on channel response estimates made for the uplink assuming a symmetrical channel. Numerical results show that the CIR estimation error could be very small if a sub-channel is considered as the minimum transmission unit. In terms of the aggregate throughput, the interference estimation method can provide a significant gain.

FIELD OF THE INVENTION

The invention generally relates to the field of wireless communications,and more specifically to reverse link OFDM (orthogonal frequencydivision multiplexing) wireless communications.

BACKGROUND OF THE INVENTION

Due to the continual growth of wireless internet, there is a high demandfor high data rate wireless transmission. Recently, to meet this demand,OFDM systems such as described in Richard Van Nee and Ramjee Prasad,OFDM for Wireless Multimedia Communications, Artech House,Boston-London, 2000 have been widely researched and developed in theIEEE standards IEEE 802.11a, Supplement to IEEE standard for InformationTechnology, Part-11: Wireless LAN Medium Access Control (MAC) andPhysical Layer (PHY) specifications, Sep. 16, 1999, and IEEE802.16-REVd/D5-2004, Draft IEEE Standard for Local and Metropolitan Areanetworks, Part 16: Air Interface for Fixed Broadband Wireless AccessSystems, May 2004. On the forward-link, these standards provideefficient solutions for high data rate transmission, using reportedcarrier-to-interference ratio (CIR) information to select properadaptive modulation coding (AMC) and active mobile stations.

SUMMARY OF THE INVENTION

For reverse link transmissions, the average interference received at abase station is estimated for each mobile station on an OFDM channel.This is used to generate an estimate of received CIR for each mobilestation. The estimated CIR can be used for many purposes such as AMCdetermination and mobile station scheduling.

According to one aspect of the present invention, there is provided amethod comprising: determining an interference estimate of aninterference component of an OFDM signal received from a mobile station;using the interference estimate, determining a carrier-to-interferenceratio (CIR) for at least one sub-carrier and/or for at least onesub-channel for the mobile station.

According to another aspect of the present invention, there is provideda method for execution by a mobile station comprising: receiving aninterference estimate of an interference component of a received versionof an OFDM signal transmitted by the mobile station; using theinterference estimate, determining a carrier-to-interference ratio (CIR)for at least one sub-carrier and/or for at least one sub-channel for themobile station.

According to still another aspect of the present invention, there isprovided an apparatus comprising: an interference estimator adapted todetermine an interference estimate of an interference component of anOFDM signal received from a mobile station; a CIR estimator adapted touse the interference estimate to determine a carrier-to-interferenceratio (CIR) for at least one sub-carrier and/or for at least onesub-channel for the mobile station.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the invention will now be described withreference to the attached drawings in which:

FIG. 1 is system view of an example interference scenario;

FIGS. 2A through 2C are flowcharts of example methods of performingcarrier-to-interference ratio estimation as provided by embodiments ofthe invention;

FIG. 3 is a plot of a PDF (probability density functions) of CIRestimation error for an example application;

FIG. 4 is an example of a TDD frame structure;

FIGS. 5 through 8 are plots showing example simulation results;

FIG. 9 is a block diagram of an example cellular communication system;

FIG. 10 is a block diagram of an example base station that might be usedto implement some embodiments of the present invention;

FIG. 11 is a block diagram of an example wireless terminal that might beused to implement some embodiments of the present invention;

FIG. 12 is a block diagram of a logical breakdown of an example OFDMtransmitter architecture that might be used to implement someembodiments of the present invention; and

FIG. 13 is a block diagram of a logical breakdown of an example OFDMreceiver architecture that might be used to implement some embodimentsof the present invention; and

FIGS. 14A-14C are block diagrams of example apparatuses for performingCIR estimation in accordance with an embodiment of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the reverse link, the interference received by a serving base stationcan change significantly over time, and the value between differenttimes can fluctuate by more than 10 dB in some systems. This is due tothe randomness with which mobile stations are transmitting their signalsusing different timing, scheduling etc.

Referring to FIG. 1, shown is an example of an interference scenario.Two sectorized BTSs (base stations) 210,212 are shown. Sector 214 ofbase station 210 is shown serving two MSs (mobile stations) 216,218.There is no interference between these two mobile stations 216,218because their transmissions are under the control of the base station210, and can be separated either in terms of time (e.g. time divisionmultiplexing) or frequency by assigning different sets of OFDMsubcarriers to each mobile station. Sector 220 of base station 212 isalso shown serving two mobile stations 222,224. Mobile stations 222,224do not interfere with each other for the same reasons described abovefor mobile stations 216,218. However, the transmissions of mobilestations 222,224 can be a source of interference to the transmissions ofmobile stations 216,218 and vice versa. Since the base station 214 andmobile stations 216,218 are not aware of how many interfering mobilestations there are, or of when the interfering mobile stations aretransmitting, it is difficult to get an accurate estimate ofinterference.

In OFDM systems, an OFDM frequency band of interest is used to transmita set of closely spaced tones referred to as sub-carriers. An OFDMsymbol is transmitted over a symbol duration. The transmit capacity ofsuch a set of sub-carriers is typically divided into sub-channels. Thereare many different sub-channel definitions. For example, a sub-channelcan be a contiguous block of sub-carriers. An example of this is theso-called AMC sub-channel defined in IEEE 802.16d. A sub-channel can bea set of blocks of sub-carriers each of which contains contiguoussub-carriers. An example of this is the so-called diversity sub-channelalso defined in IEEE 802.16d. A sub-channel can be a set of sub-carriersthat are scattered throughout the entire OFDM frequency band. An exampleof this is the so-called FUSC (full usage of sub-channel) also definedin IEEE 802.16d. A sub-channel can be a set of sub-carriers that arescattered throughout only a part of the entire OFDM frequency band. Anexample of this is the so-called PUSC (partial usage of sub-channel)also defined in IEEE 802.16d.

Typically, each transmitting mobile station is assigned one or multiplesub-channels. The sub-channel definition in adjacent coverage areas maybe the same or different. The assignment of sub-channels to mobilestations will typically vary from symbol to symbol. In some sub-channeldefinitions, the sub-channels with the same index in different sectorsconsist of different sub-carriers due to the different initializationwhich gives different sub-channel patterns. Therefore, the user receivesinterferences over a sub-channel that come from many users.

In OFDM systems, while the interference on a particular sub-carrier isun-predictable, the interference averaged over a set of carriers forminga sub-channel can be relatively stable and can be predicted based onprevious received interferences.

Referring now to FIG. 2A, an example interference estimation methodprovided by an embodiment of the invention will now be described. Forthe embodiment of FIG. 2A, there is no specificity as to where each ofthe steps are implemented. For example, they can be implemented by an MSor a BTS as may be appropriate for a given application. FIGS. 2B and 2Care specific examples of how the steps might be implemented in TDD (timedivision duplex) and FDD (frequency division duplex) systems,respectively.

The method begins at step 2A-1 with initializing the estimatedinterference to be zero (dB) for each individual mobile station. At step2A-2, based on the signals received during an OFDM frame (defined to besome number of OFDM symbols) on active sub-channels, an averageinterference level for each mobile station is determined. Preferably, along term average is generated by combining the current values withprevious interference estimates, for example by using a linear filter.At step 2A-3, a channel estimate is generated for each mobile stationand for each sub-carrier. At step 2A-4, using the estimated channelresponse and reported interference, an estimated CIR is determined foreach MS, and preferably for each individual sub-carrier and then foreach sub-channel. The estimated CIR is then available for use, forexample for AMC determination and/or channel selection.

Referring now to FIG. 2B, an example interference estimation methodprovided by an embodiment of the invention will now be described that isparticularly applicable to a TDD environment. Steps 2B-1 and 2B-2 arethe same as steps 2A-1 and 2A-2 described above. At step 2B-3, the BTSreports the interference estimate to each mobile station. At step 2B-4,the MS determines channel response for the downlink for eachsub-carrier. In a TDD system, the channel response is symmetrical, sothe downlink channel response can be used as estimates for the uplink.At step 2B-5, using the estimated channel response and reportedinterference, each mobile station determines an estimated CIR for eachindividual sub-carrier and then for each sub-channel. The estimated CIRis then available for use, for example for AMC determination and/ormobile station.

Referring now to FIG. 2C, an example interference estimation methodprovided by an embodiment of the invention will now be described that isparticularly applicable to an FDD environment. Note that this approachcan also applied in a TDD environment. Steps 2C-1 and 2C-2 are the sameas steps 2A-1 and 2A-2 described above. At step 2C-3, the BTS estimatesa channel response for each mobile station and each sub-carrier. At step2C-4, using the estimated channel response and reported interference,each BTS determines an estimated CIR for each individual sub-carrier andthen for each sub-channel. At step 2C-5, the estimated CIR is reportedto the mobile station. The estimated CIR is then available for use, forexample for AMC determination and/or mobile station.

The following is a mathematical formulation of an example implementationof the interference estimation method.

The received power for the desired signal component (i.e. not includingthe interfering components) for the k-th mobile station on the i-thsub-carrier and the l-th sub-channel in the m-th frame is P_(k,i,l)(m).

The received power of interference and noise for the k-th mobile stationon the i-th sub-carrier and the l-th sub-channel in the m-th frame isI_(k,i,l)(m).

The actual average CIR for the k-th mobile station on the i-thsub-carrier and the 1-th sub-channel in the m-th frame is Γ_(k,i,l)(m).This can be expressed as follows:

${\Gamma_{k,i,l}(m)} = \frac{P_{k,i,{l{(m)}}}}{I_{k,i,{l{(m)}}} + N_{o}}$

where P_(k,i,l)(m) is the signal power, I_(k,i,l)(m) is the interferencepower and N_(o) is the noise which will be discounted in the math thatfollows as it is an easily removable contribution. Using the CIR,I_(k,i,l)(m) can be expressed as

${I_{k,i,l}(m)} = {\frac{P_{k,i,l}(m)}{\Gamma_{k,i,l}(m)}.}$

More practically, I_(k,i,l)(m) can be expressed in terms of a totalreceived power P_(received,k,i,l)(m) on a particular sub-carrier and thedesired signal component power P_(k,i,l)(m) as follows:

P _(received,k,i,l)(m)=I _(k,i,l)(m)+P _(k,i,l)(m)

This can be rearranged to yield the following expression forI_(k,i,l)(m):

I _(k,i,l)(m)=P _(received,k,i,l)(m)−P _(k,i,l)(m)

In the above expression, P_(received,k,i,l)(m) is measurable at thereceiver, and P_(k,i,l)(m) can determined from pilot channel signalstrength measurements. For example, in each sub-channel, there may bedata tones and pilot tones depending on sub-channelization type. Forexample, in IEEE 802.16d, the AMC sub-channel consists of 48 data tonesand 24 pilot tones. Those pilot tones can be used for many purposes suchas signal strength measurements and channel response estimation. Theinterpolation between neighboring pilot tones is used to figure out theinformation for data tone.

The received power of interference and noise averaged over Nsub-carriers and L sub-channels for the k-th mobile station in the m-thframe is Ī_(k)(m) and can expressed as

${{\overset{\_}{I}}_{k}(m)} = {\frac{1}{LN}{\sum\limits_{l = 0}^{L - 1}\; {\sum\limits_{i = 0}^{N - 1}\; {{I_{k,i,j}(m)}.}}}}$

The pilot sub-carriers are preferably omitted from this calculation. Ifthe pilot sub-carriers are omitted, then the above expression can besimplified to:

${{\overset{\_}{I}}_{l}(m)} = {\frac{1}{LN}\left( {P_{{received},{tot}} - P_{{desired\_ signal},{tot}}} \right)}$

where P_(received,tot) is the total received power over the Nsub-carriers and L sub-channels for the k-th mobile station,P_(received,pilot) is the total received pilot power over the Nsub-carriers and L sub-channels for the k-th mobile station, P_(desired)_(—) _(signal,tot) is the total received desired signal power over the Nsub-carriers and L sub-channels for the k-th mobile station.

The estimated power of interference and noise for the k-th mobilestation in the (m+1)-th frame is Î_(k)(m+1), which can be represented bya linear filter

Î _(k)(m+1)=Î _(k)(m)·(1−α)+Ī _(k)(m)·α

where α is a filter coefficient and 0<α≦1. Other filterdesigns/extrapolation designs can be employed.

The estimated CIR for the k-th mobile station on the i-th sub-carrierand the l-th sub-channel in the (m+1)-th frame is {circumflex over(Γ)}_(k,i,l)(m+1) and can be calculated as

${{\hat{\Gamma}}_{k,i,l}(m)} = {\frac{{\overset{\sim}{P}}_{k,i,l}(m)}{{\hat{I}}_{k}(m)}.}$

where {tilde over (P)}_(k,i,l)(m) is the reported or estimated desiredsignal component power for the k-th mobile station on the i-thsub-carrier and the l-th sub-channel in the m-th frame. The estimatedCIR for the k-th mobile station on the l-th sub-channel in the (m+1)-thframe is {circumflex over (Γ)}_(k,l)(m+1) and can be calculated as

${{\hat{\Gamma}}_{k,l}(m)} = {\frac{\sum\limits_{i = 0}^{N - 1}\; {{\overset{\sim}{P}}_{k,i,l}(m)}}{N \cdot {{\hat{I}}_{k}(m)}}.}$

As indicated above, the transmissions from each mobile station includeone or more pilot sub-carriers. When the BTS receives the pilots, therewill also usually be interference from the mobile stations served byneighboring sector. An exception to this is PUSC where neighbouringsectors use different sets of sub-carriers. The pilot sub-carriers areused in order to estimate the channel for the pilot sub-carriers, andinterpolation can be performed to determine the channel for everysub-carrier.

Note that {tilde over (P)}_(k,i,l)(m) can be determined based onreceived pilots by subtracting the channel response from a knowntransmit power. This channel response information can be forwarded tothe mobile station, and the mobile station will know the power it usedto transmit. Alternatively, the base station may also know the powerthat the mobile station used to transmit if it is controlling that powerthrough power control.

In a particular example, each mobile station transmits using the samepower on all sub-carriers, in which case the transmit power is a singlevalue C_(k)(m) (i.e. for kth mobile station during mth frame). Thisvalue may be subject to power control in some implementations. The basestation can then determine {tilde over (P)}_(k,i,l)(m) according to{tilde over (P)}_(k,i,l)(m)=C_(k)(m)·H_(k,i,l)(m), where H_(k,i,l)(m) isthe channel response information. Alternatively, the mobile station canmake this determination if the channel information is fed back from thebase station, or can be derived from other information fed back from thebase station.

Interference estimation for a given mobile station is based oninterference measurements/estimates for the assignedsub-carriers/sub-channels of the previous frame in combination withearlier estimates. CIR estimates on the other hand can be generated foreither currently assigned sub-carriers/sub-channels, for example toassist in AMC decisions, or for potentially assignedsub-carriers/sub-channels, to assist in sub-channel selection forexample.

In other words, the CIR estimate can be determined for a different setof sub-channels/sub-carriers than was used in generating theinterference estimate.

If the CIR calculation is done in the MS, MS knows transmit signalstrengths and can interpolate previous channel responses to get channelresponse estimates for currently/potentially assignedsub-carriers/sub-channels to get the desired signal strength needed forthe CIR calculation. In a TDD system, the MS can do this calculationusing channel responses estimated for the uplink since there is asymmetrical channel and hence no channel response feedback is needed.

If the CIR calculation is done by BTS, the BTS needs to make some sortof assumption on transmitted signal strength or otherwise be able todetermine the desired signal strength. For example, the BTS might use aknown transmit signal strength C, and the interpolated channel responseto get desired signal strength needed for the CIR calculation. In thiscase, BTS estimates the interference and received signal power, and thenfigures out the average CIR over all the available tones. This CIR willbe sent back to MS.

Performance Evaluation

For purposes of performance evaluation of the above derivation, one canassume that the received interference for both real and imaginary partson each carrier is Gaussian distributed with standard deviations of σ.Averaging M interferences obtains a complex number with the standarddeviation of σ/√{square root over (M)} for both parts, resulting in thevariance of interference of (2−π/2)·σ²/M. This shows that increasing Mwill linearly decrease the variance of received interference.

To evaluate how accurate CIR estimation is on each sub-carrier and eachsub-channel, an estimation error per sub-carrier is defined as:

Δ_(sub-carrier)=Γ_(sub-carrier) ^((real))−Γ_(sub-carrier) ^((est))

and per sub-channel as:

Δ_(sub-carrier)=Γ_(sub-channel) ^((real))−Γ_(sub-channel) ^((est))

where Γ_(sub-carrier), Γ_(sub-carrier) ^((est)), Γ_(sub-channel)^((real)) and Γ_(sub-channel) ^((est)) represent the real received CIRand estimated CIR per sub-carrier and sub-channel, respectively.

FIG. 3 shows an example of CIR estimation error between real andestimated CIR for both sub-carrier and sub-channel in the context of anexample system described below. From the results of FIG. 3, twoobservations can be made. First, it can be seen that the standarddeviation for sub-carriers is about 6.56 dB while the standard deviationfor sub-channels (each sub-channel is composed of 48 sub-carriers) isabout 2.42 dB. The CIR estimation error for each sub-channel is muchsmaller than the error for each sub-carrier. This small estimation errormay not seriously impact the system level performance due to ARQ(automatic repeat request) processes which may be employed to completelyrecover some incorrect packets after several retransmissions. Second,the sub-carrier CIR estimation error is extremely high when the receivedsub-carrier CIR is low. This means that the interference estimation willwork best in a higher received sub-carrier CIR region when sub-carrierCIR estimation is required. For sub-channel CIR estimation, however,there is no such a limitation.

System Level Performance

In order to investigate the performance with the proposed interferenceestimation method, system level simulation based on IEEE 806.16-REVdstandard assumptions were performed. In the following, a frame structurefor OFDM is described. Then, the simulation assumptions are listed.Finally, the simulation results are presented with detailed discussions.

Frame Structure

The TDD system is based on wireless MAN-OFDMA PHY in IEEE 806.16-REVdstandard and its frame structure with 5 msec frame length is illustratedin FIG. 4.

A detailed frame configuration in terms of the number of symbols,preambles, dedicated control symbols, data symbols is listed in Table 1below.

TABLE 1 Frame configuration of TDD OFDMA system for 5 msec frame.Forward- Reverse- Frame Configuration Link Link Number of Symbols 27 15Number of Preambles 2 0 Number Dedicated Control 1 3 Symbols DataSymbols 24 12 Transmission Time 3.1104 ms 1.728 ms TDD Protection Time121.2 μs 40.4 μs Effective Bandwidth 6.3824 MHz 3.6176 MHz

Simulation Assumptions

The simulation focuses on the reverse-link and its system levelsimulation assumptions are listed in Table 2.

TABLE 2 System level simulation assumptions. Number of Cells 19 Numberof mobile 20 stations FFT/IFFT Size 1024 Antenna Structure 1 × 1Feedback Delay 1 TDD Frame Maximum Retransmission 3 Number EntireBandwidth 10 MHz Center Frequency 2.3 GHz Transmission Power 200 mWatts(23 dBm) Noise Figure 9 dB Antenna Gain −1 dBi Maximum CIR 30 dB FilterCoefficient α 0.5

The relation of AMC determination in terms of channel encoding blocklength, modulation, channel code rate, and data transmission rate islisted in Table 3.

TABLE 3 AMC set assumption. Channel Number of Encoding Block Sub-Modulation Channel Length (bits) channels Method Code Rate 480 10 QPSK ⅕480 10 QPSK ¼ 480 10 QPSK ⅓ 720 15 QPSK ½ 720 15 QPSK ⅔ 960 20 QPSK ¾960 20 QPSK ⅘ 1440 30 16QAM ½ 1440 30 16QAM ⅔ 1920 40 16QAM ¾ 2160 4516QAM ⅘ 2880 60 64QAM ⅔ 2880 60 64QAM ¾ 3600 75 64QAM ⅘The path-loss model based on ITU vehicular model is represented as

L=40×(1−4×10⁻³×15)−log₁₀R−18×log₁₀15+21×log₁₀(2.3×10³)+80

where R is the distance between BTS and mobile station in km.

Link-Level Curves for AMC

FIG. 5 shows the link-level code sets in terms of BLER versus SNR for a1×1 structure.

Channel Model and CIR Generation

A mixed channel model with assignment probability as listed in Table 4is considered in our system level simulation.

TABLE 4 Channel Model. Channel # of Speed Fading Assignment Modelfingers (km/h) Model Probability Model A 4 3 JTC 0.2 Model B 4 10 JTC0.2 Model C 6 3 JTC 0.15 Model D 6 10 JTC 0.15 Model E 6 60 JTC 0.3The fading channel generation is based on a JTC model. The CIRcalculation is performed on the frequency domain and individuallygenerated for each OFDM tone.

Mobile Station Scheduler and Channel Permutation

Mobile station scheduler for resource allocation is based on eitherround-robin (RR) or proportional fairness (PF).

Several permutation patterns are used to form the sub-channel asfollows:

Permutation-1: This symbol structure (mandatory and diversity channel)supports 35 sub-channels where each transmission uses 48 data carriersas the minimal block of processing. A burst is composed of 3 timesymbols and 1 sub-channel, within each burst there are 48 datasub-carriers and 24 fixed-location pilot sub-carriers.Permutation-2: This symbol structure (optional and diversity channel)supports 48 sub-channels where a sub-channel consists of 48 datacarriers and 6 pilot carriers. A burst is composed of 3 time symbols and1 sub-channel, within each burst there are 48 data sub-carriers and 6fixed-location pilot sub-carriers.Permutation-3: This symbol structure belongs to AMC channel. Sub-channelconsists of 48 data carriers or 6 contiguous bins. The bin is the set of9 contiguous sub-carriers within an OFDMA symbol.

Performance Discussion

FIG. 6 shows the CDF (cumulative distribution function) of mobilestation throughput when we employ 1×1 antenna structure on thereverse-link. It can be seen that the data transmission based oninterference estimation method is much better than that withoutinterference estimation. The gain could reach 3.7 if we employround-robin scheduling and 2.7 if proportional fairness scheduling.

FIG. 7 shows the fairness curves with and without interferenceestimation when we utilize permutation-2 channel. We may find that thedata transmission with interference estimation and proportional fairnessscheduling provides the best result but slightly has some degradation onmobile station throughput (see FIG. 6).

FIG. 8 shows the received sub-channel CIR for each mobile station whenwe utilize the permutation-2 channel. It can be found that the datatransmission with interference estimation and round-robin experiencesthe best channels while the data transmission with round-robin and nointerference estimation experiences the worst channels. This is becausethe former provides more accurate AMC determination than the latter.

Table 5 and Table 6 list the aggregate throughput per sector andresidual FER when we employ different schedulers (round-robin,interference estimation round-robin and interference estimationproportional fairness) and different channel (permutation-1,permutation-2 and permutation-3), respectively. It can be seen that therelative gain achieved by interference estimation approach on threepermutation channels are almost the same and between 3 and 4 times asopposed to no interference estimation transmission.

TABLE 5 Aggregate mobile station throughput with difference channels andschedulers. Permutation-1 Permutation-2 (Diversity (DiversityPermutation-3 Channel) Channel) (AMC Channel) RR 310.65 1117.98 1055.15Interference 1029.96 4117.68 2919.54 Estimate RR Interference 1097.763100.45 2136.73 Estimate PF

TABLE 6 Residual FER with difference channels and schedulers.Permutation-1 Permutation-2 (Diversity (Diversity Permutation-3 Channel)Channel) (AMC Channel) RR 0.3782 0.4087 0.4206 Interference 0.13460.1068 0.1239 Estimate RR Interference 0.1191 0.0876 0.1467 Estimate PF

For the purposes of providing context for embodiments of the inventionfor use in a communication system, FIG. 9 shows a base stationcontroller (BSC) 10 which controls wireless communications withinmultiple cells 12, which cells are served by corresponding base stations(BS) 14. In general, each base station 14 facilitates communicationsusing OFDM with mobile and/or wireless terminals 16, which are withinthe cell 12 associated with the corresponding base station 14. Themovement of the mobile terminals 16 in relation to the base stations 14results in significant fluctuation in channel conditions. Asillustrated, the base stations 14 and mobile terminals 16 may includemultiple antennas to provide spatial diversity for communications.

A high level overview of the mobile terminals 16 and base stations 14upon which aspects of the present invention are implemented is providedprior to delving into the structural and functional details of thepreferred embodiments. With reference to FIG. 10, an example basestation 14 is illustrated. The base station 14 generally includes acontrol system 20, a baseband processor 22, transmit circuitry 24,receive circuitry 26, multiple antennas 28, and a network interface 30.The receive circuitry 26 receives radio frequency signals bearinginformation from one or more remote transmitters provided by mobileterminals 16 (illustrated in FIG. 9). Preferably, a low noise amplifierand a filter (not shown) cooperate to amplify and remove broadbandinterference from the signal for processing. Downconversion anddigitization circuitry (not shown) will then downconvert the filtered,received signal to an intermediate or baseband frequency signal, whichis then digitized into one or more digital streams.

The baseband processor 22 processes the digitized received signal toextract the information or data bits conveyed in the received signal.This processing typically involves demodulation, decoding, and errorcorrection operations. As such, the baseband processor 22 is generallyimplemented in one or more digital signal processors (DSPs) orapplication-specific integrated circuits (ASICs). The receivedinformation is then sent across a wireless network via the networkinterface 30 or transmitted to another mobile terminal 16 serviced bythe base station 14.

On the transmit side, the baseband processor 22 receives digitized data,which may represent voice, data, or control information, from thenetwork interface 30 under the control of control system 20, and encodesthe data for transmission. The encoded data is output to the transmitcircuitry 24, where it is modulated by a carrier signal having a desiredtransmit frequency or frequencies. A power amplifier (not shown) willamplify the modulated carrier signal to a level appropriate fortransmission, and deliver the modulated carrier signal to the antennas28 through a matching network (not shown). Modulation and processingdetails are described in greater detail below.

With reference to FIG. 11, an example mobile terminal 16 configuredaccording to one embodiment of the present invention is illustrated.Similarly to the base station 14, the mobile terminal 16 will include acontrol system 32, a baseband processor 34, transmit circuitry 36,receive circuitry 38, multiple antennas 40, and user interface circuitry42. The receive circuitry 38 receives radio frequency signals bearinginformation from one or more base stations 14. Preferably, a low noiseamplifier and a filter (not shown) cooperate to amplify and removebroadband interference from the signal for processing. Downconversionand digitization circuitry (not shown) will then downconvert thefiltered, received signal to an intermediate or baseband frequencysignal, which is then digitized into one or more digital streams.

The baseband processor 34 processes the digitized received signal toextract the information or data bits conveyed in the received signal.This processing typically involves demodulation, decoding, and errorcorrection operations. The baseband processor 34 is generallyimplemented in one or more digital signal processors (DSPs) andapplication specific integrated circuits (ASICs).

For transmission, the baseband processor 34 receives digitized data,which may represent voice, data, or control information, from thecontrol system 32, which it encodes for transmission. The encoded datais output to the transmit circuitry 36, where it is used by a modulatorto modulate a carrier signal that is at a desired transmit frequency orfrequencies. A power amplifier (not shown) will amplify the modulatedcarrier signal to a level appropriate for transmission, and deliver themodulated carrier signal to the antennas 40 through a matching network(not shown). Various modulation and processing techniques available tothose skilled in the art are used for signal transmission between themobile terminal and the base station.

In OFDM modulation, the transmission band is divided into multiple,orthogonal carrier waves. Each carrier wave is modulated according tothe digital data to be transmitted. Because OFDM divides thetransmission band into multiple carriers, the bandwidth per carrierdecreases and the modulation time per carrier increases. Since themultiple carriers are transmitted in parallel, the transmission rate forthe digital data, or symbols, on any given carrier is lower than when asingle carrier is used.

OFDM modulation utilizes the performance of an Inverse Fast FourierTransform (IFFT) on the information to be transmitted. For demodulation,the performance of a Fast Fourier Transform (FFT) on the received signalrecovers the transmitted information. In practice, the IFFT and FFT areprovided by digital signal processing carrying out an Inverse DiscreteFourier Transform (IDFT) and Discrete Fourier Transform (DFT),respectively. Accordingly, the characterizing feature of OfDM modulationis that orthogonal carrier waves are generated for multiple bands withina transmission channel. The modulated signals are digital signals havinga relatively low transmission rate and capable of staying within theirrespective bands. The individual carrier waves are not modulateddirectly by the digital signals. Instead, all carrier waves aremodulated at once by IFFT processing.

In operation, OFDM is preferably used for at least downlink transmissionfrom the base stations 14 to the mobile terminals 16. Each base station14 is equipped with “n” transmit antennas 28, and each mobile terminal16 is equipped with “m” receive antennas 40. Notably, the respectiveantennas can be used for reception and transmission using appropriateduplexers or switches and are so labeled only for clarity.

With reference to FIGS. 9 and 12, an example logical OFDM transmissionarchitecture will be described. Initially, the base station controller10 will send data to be transmitted to various mobile terminals 16 tothe base station 14. The base station 14 may use the channel qualityindicators (CQIs) associated with the mobile terminals to schedule thedata for transmission as well as select appropriate coding andmodulation for transmitting the scheduled data. The CQIs may be directlyfrom the mobile terminals 16 or determined at the base station 14 basedon information provided by the mobile terminals 16. In either case, theCQI for each mobile terminal 16 is a function of the degree to which thechannel amplitude (or response) varies across the OFDM frequency band.

Scheduled data 44, which is a stream of bits, is scrambled in a mannerreducing the peak-to-average power ratio associated with the data usingdata scrambling logic 46. A cyclic redundancy check (CRC) for thescrambled data is determined and appended to the scrambled data usingCRC adding logic 48. Next, channel coding is performed using channelencoder logic 50 to effectively add redundancy to the data to facilitaterecovery and error correction at the mobile terminal 16. Again, thechannel coding for a particular mobile terminal 16 is based on the CQI.In some implementations, the channel encoder logic 50 uses known Turboencoding techniques. The encoded data is then processed by rate matchinglogic 52 to compensate for the data expansion associated with encoding.

Bit interleaver logic 54 systematically reorders the bits in the encodeddata to minimize the loss of consecutive data bits. The resultant databits are systematically mapped into corresponding symbols depending onthe chosen baseband modulation by mapping logic 56. Preferably,Quadrature Amplitude Modulation (QAM) or Quadrature Phase Shift Key(QPSK) modulation is used. The degree of modulation is preferably chosenbased on the CQI for the particular mobile terminal. The symbols may besystematically reordered to further bolster the immunity of thetransmitted signal to periodic data loss caused by frequency selectivefading using symbol interleaver logic 58.

At this point, groups of bits have been mapped into symbols representinglocations in an amplitude and phase constellation. When spatialdiversity is desired, blocks of symbols are then processed by space-timeblock code (STC) encoder logic 60, which modifies the symbols in afashion making the transmitted signals more resistant to interferenceand more readily decoded at a mobile terminal 16. The STC encoder logic60 will process the incoming symbols and provide “n” outputscorresponding to the number of transmit antennas 28 for the base station14. The control system 20 and/or baseband processor 22 as describedabove with respect to FIG. 2 may provide a mapping control signal tocontrol STC encoding. At this point, assume the symbols for the “n”outputs are representative of the data to be transmitted and capable ofbeing recovered by the mobile terminal 16.

For the present example, assume the base station 14 has two antennas 28(n=2) and the STC encoder logic 60 provides two output streams ofsymbols. Accordingly, each of the symbol streams output by the STCencoder logic 60 is sent to a corresponding IFFT processor 62,illustrated separately for ease of understanding. Those skilled in theart will recognize that one or more processors may be used to providesuch digital signal processing, alone or in combination with otherprocessing described herein. The IFFT processor 62 will preferablyoperate on the respective symbols to provide an inverse FourierTransform. The output of the IFFT processor 62 provides symbols in thetime domain. The time domain symbols are grouped into frames, which areassociated with a prefix by prefix insertion logic 64. Each of theresultant signals is up-converted in the digital domain to anintermediate frequency and converted to an analog signal via thecorresponding digital up-conversion (DUC) and digital-to-analog (D/A)conversion circuitry 66. The resultant (analog) signals are thensimultaneously modulated at the desired RF frequency, amplified, andtransmitted via the RF circuitry 68 and antennas 28. Notably, pilotsignals known by the intended mobile terminal 16 are scattered among thesub-carriers. The mobile terminal 16, which is discussed in detailbelow, will use the pilot signals for channel estimation.

Reference is now made to FIG. 13 to illustrate reception of thetransmitted signals by a mobile terminal 16. Upon arrival of thetransmitted signals at each of the antennas 40 of the mobile terminal16, the respective signals are demodulated and amplified bycorresponding RF circuitry 70. For the sake of conciseness and clarity,only one of the two receive paths is described and illustrated indetail. Analog-to-digital (A/D) converter and down-conversion circuitry72 digitizes and downconverts the analog signal for digital processing.The resultant digitized signal may be used by automatic gain controlcircuitry (AGC) 74 to control the gain of the amplifiers in the RFcircuitry 70 based on the received signal level.

Initially, the digitized signal is provided to synchronization logic 76,which includes coarse synchronization logic 78, which buffers severalOFDM symbols and calculates an auto-correlation between the twosuccessive OFDM symbols. A resultant time index corresponding to themaximum of the correlation result determines a fine synchronizationsearch window, which is used by fine synchronization logic 80 todetermine a precise framing starting position based on the headers. Theoutput of the fine synchronization logic 80 facilitates frameacquisition by frame alignment logic 84. Proper framing alignment isimportant so that subsequent FFT processing provides an accurateconversion from the time domain to the frequency domain. The finesynchronization algorithm is based on the correlation between thereceived pilot signals carried by the headers and a local copy of theknown pilot data. Once frame alignment acquisition occurs, the prefix ofthe OFDM symbol is removed with prefix removal logic 86 and resultantsamples are sent to frequency offset correction logic 88, whichcompensates for the system frequency offset caused by the unmatchedlocal oscillators in the transmitter and the receiver. Preferably, thesynchronization logic 76 includes frequency offset and clock estimationlogic 82, which is based on the headers to help estimate such effects onthe transmitted signal and provide those estimations to the correctionlogic 88 to properly process OFDM symbols.

At this point, the OFDM symbols in the time domain are ready forconversion to the frequency domain using FFT processing logic 90. Theresults are frequency domain symbols, which are sent to processing logic92. The processing logic 92 extracts the scattered pilot signal usingscattered pilot extraction logic 94, determines a channel estimate basedon the extracted pilot signal using channel estimation logic 96, andprovides channel responses for all sub-carriers using channelreconstruction logic 98. In order to determine a channel response foreach of the sub-carriers, the pilot signal is essentially multiple pilotsymbols that are scattered among the data symbols throughout the OFDMsub-carriers in a known pattern in both time and frequency. Continuingwith FIG. 13, the processing logic compares the received pilot symbolswith the pilot symbols that are expected in certain sub-carriers atcertain times to determine a channel response for the sub-carriers inwhich pilot symbols were transmitted. The results are interpolated toestimate a channel response for most, if not all, of the remainingsub-carriers for which pilot symbols were not provided. The actual andinterpolated channel responses are used to estimate an overall channelresponse, which includes the channel responses for most, if not all, ofthe sub-carriers in the OFDM channel.

The frequency domain symbols and channel reconstruction information,which are derived from the channel responses for each receive path areprovided to an STC decoder 100, which provides STC decoding on bothreceived paths to recover the transmitted symbols. The channelreconstruction information provides equalization information to the STCdecoder 100 sufficient to remove the effects of the transmission channelwhen processing the respective frequency domain symbols

The recovered symbols are placed back in order using symbolde-interleaver logic 102, which corresponds to the symbol interleaverlogic 58 of the transmitter. The deinterleaved symbols are thendemodulated or de-mapped to a corresponding bitstream using de-mappinglogic 104. The bits are then de-interleaved using bit de-interleaverlogic 106, which corresponds to the bit interleaver logic 54 of thetransmitter architecture. The de-interleaved bits are then processed byrate de-matching logic 108 and presented to channel decoder logic 110 torecover the initially scrambled data and the CRC checksum. Accordingly,CRC logic 112 removes the CRC checksum, checks the scrambled data intraditional fashion, and provides it to the de-scrambling logic 114 forde-scrambling using the known base station de-scrambling code to recoverthe originally transmitted data 116.

In parallel to recovering the data 116, a CQI, or at least informationsufficient to create a CQI at the base station 14, is determined andtransmitted to the base station 14. As noted above, the CQI may be afunction of the carrier-to-interference ratio (CR), as well as thedegree to which the channel response varies across the varioussub-carriers in the OFDM frequency band. For this embodiment, thechannel gain for each sub-carrier in the OFDM frequency band being usedto transmit information is compared relative to one another to determinethe degree to which the channel gain varies across the OFDM frequencyband. Although numerous techniques are available to measure the degreeof variation, one technique is to calculate the standard deviation ofthe channel gain for each sub-carrier throughout the OFDM frequency bandbeing used to transmit data.

FIGS. 9 to 13 provide one specific example of a communication systemthat could be used to implement embodiments of the invention. It is tobe understood that embodiments of the invention can be implemented withcommunications systems having architectures that are different than thespecific example, but that operate in a manner consistent with theimplementation of the embodiments as described herein.

Referring now to FIG. 14A, shown is a block diagram of an exampleapparatus for performing CIR estimation in accordance with an embodimentof the invention. The apparatus has an interference estimator 300adapted to determine an interference estimate of an interferencecomponent of an OFDM signal received from a mobile station, and a CIRestimator 304 adapted to use the interference estimate to determine acarrier-to-interference ratio (CIR) for at least one sub-carrier and/orfor at least one each sub-channel for the mobile station. Theinterference estimator 300 passes the interference estimates to the CIRestimator 304 as indicated at 302.

FIG. 14B is a particular implementation of the apparatus of claim 14A.The interference estimator 300 is part of a base station 306, and theCIR estimator 304 is part of a mobile station 308. The mobile stationalso has a channel estimator 310 that performs channel estimation of adownlink channel. The CIR estimator uses the downlink channel estimatesas if they were uplink channel estimates. This assumes that there is asymmetrical channel.

FIG. 14C is another particular implementation of the apparatus of claim14A. The interference estimator 300 is part of a base station 320, andthe CIR estimator 304 is also part of the mobile station 320. The basestation 320 also has a channel estimator 322 that performs channelestimation of an uplink channel. The CIR estimator 304 uses the uplinkchannel estimates to produce the CIR estimates that are then forwardedat 324 to the mobile station.

For the embodiments of FIGS. 14A, 14B and 14C, a particular layout offunctionality has been shown, but it is to be understood that thesefunctions can be combined, or arranged differently than shown. Thefunctions can be implemented using any suitable one or combination ofhardware, software and/or firmware.

Numerous modifications and variations of the present invention arepossible in light of the above teachings. It is therefore to beunderstood that within the scope of the appended claims, the inventionmay be practiced otherwise than as specifically described herein.

1-21. (canceled)
 22. A method for estimating a carrier-to-interferenceratio (CIR) in an OFDM system, the method comprising: a mobile stationtransmitting an OFDM signal to a base station; the mobile stationreceiving an interference estimate corresponding to the OFDM signal,wherein the interference estimate is received from the base station; themobile station determining a CIR for at least one sub-carrier and/or forat least on sub-channel for the mobile station using the interferenceestimate.
 23. The method of claim 22, further comprising: the mobilestation determining downlink channel measurements, the downlink channelestimates being representative of uplink channel estimates; wherein saiddetermining the CIR is performed using the downlink channel estimates.24. The method of claim 23, wherein said determining the CIR comprises:determining a desired signal power by subtracting the respective channelestimate from a transmitted signal power for each sub-carrier used bythe mobile station.
 25. The method of claim 24, wherein said determiningthe CIR further comprises: determining the CIR for each sub-carrier bydividing the desired signal power by the interference estimate.
 26. Themethod of claim 24, wherein said determining the CIR further comprises:determining the CIR for each sub-channel by summing desired signalpowers of sub-carriers of the sub-channel and dividing the sum by theinterference estimate.
 27. The method of claim 22, wherein theinterference estimate comprises a long-term average of a plurality ofinterference estimates.
 28. The method of claim 22, wherein theinterference estimate is generated based on signals received during anOFDMA frame on sub-channels associated with the mobile station.
 29. Themethod of claim 22, further comprising: using the CIR to performsub-channel selection.
 30. The method of claim 22, further comprising:using the ICIR to perform adaptive modulation and coding (AMC).
 31. Amobile station configured to estimate a carrier-to-interference ratio(CIR) in an OFDM system, the mobile station comprising: wirelesscommunication circuitry, configured to perform wireless communicationwith a base station; and processing hardware coupled to the wirelesscommunication circuitry, wherein the processing hardware is configuredto operate with the wireless communication circuitry to: transmit anOFDM signal to the base station; receive an interference estimatecorresponding to the OFDM signal, wherein the interference estimate isreceived from the base station; determine a CIR for at least onesub-carrier and/or for at least on sub-channel for the mobile stationusing the interference estimate.
 32. The mobile station of claim 31,wherein the processing hardware is further configured to: determinedownlink channel measurements, the downlink channel estimates beingrepresentative of uplink channel estimates; wherein said determining theCIR is performed using the downlink channel estimates.
 33. The mobilestation of claim 32, wherein said determining the CIR comprises:determining a desired signal power by subtracting the respective channelestimate from a transmitted signal power for each sub-carrier used bythe mobile station; and determining the CIR for each sub-carrier bydividing the desired signal power by the interference estimate.
 34. Themobile station of claim 32, wherein said determining the CIR furthercomprises: determining a desired signal power by subtracting therespective channel estimate from a transmitted signal power for eachsub-carrier used by the mobile station; and determining the CIR for eachsub-channel by summing desired signal powers of sub-carriers of thesub-channel and dividing the sum by the interference estimate.
 35. Themobile station of claim 31, wherein the interference estimate comprisesa long-term average of a plurality of interference estimates.
 36. Themobile station of claim 31, wherein the processing hardware is furtherconfigured to: using the CIR to perform sub-channel selection.
 37. Themobile station of claim 31, wherein the processing hardware is furtherconfigured to: using the ICIR to perform adaptive modulation and coding(AMC).
 38. A non-transitory, computer accessible memory medium storingprogram instructions for estimating a carrier-to-interference ratio(CIR) in an OFDM system, wherein the program instructions are executableby a processor to: transmit an OFDM signal to a base station; receive aninterference estimate corresponding to the OFDM signal, wherein theinterference estimate is received from the base station; determine a CIRfor at least one sub-carrier and/or for at least on sub-channel for themobile station using the interference estimate.
 39. The non-transitory,computer accessible memory medium of claim 38, wherein the processinghardware is further configured to: determine downlink channelmeasurements, the downlink channel estimates being representative ofuplink channel estimates; wherein said determining the CIR is performedusing the downlink channel estimates.
 40. The non-transitory, computeraccessible memory medium of claim 39, wherein said determining the CIRcomprises: determining a desired signal power by subtracting therespective channel estimate from a transmitted signal power for eachsub-carrier used by the mobile station; and determining the CIR for eachsub-carrier by dividing the desired signal power by the interferenceestimate.
 41. The non-transitory, computer accessible memory medium ofclaim 39, wherein said determining the CIR further comprises:determining a desired signal power by subtracting the respective channelestimate from a transmitted signal power for each sub-carrier used bythe mobile station; and determining the CIR for each sub-channel bysumming desired signal powers of sub-carriers of the sub-channel anddividing the sum by the interference estimate.